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Record W2760454969

Reconciling competing values of urban open space in two national capitals

2015· article· en· W2760454969 on OpenAlexaboutno aff
Andrew MacKenzie

Bibliographic record

VenueUniversity of Canberra Research Portal · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationUrban planningCultural heritageProject commissioningMetropolitan areaSpace (punctuation)Environmental planningGovernment (linguistics)PublishingEconomic growthPolitical scienceEnvironmental resource managementGeographyCivil engineeringEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

Protecting the heritage values of urban open space in the face of significant change to the surrounding urban structure highlights a particular tension between two apparently conflicting goals of sustainable development. On one hand the imagined city of the future is more compact as urban designers, planners and urban researchers advocate to increase the density of cities. On the other hand, large tracts of urban open space, left undeveloped for its scenic quality, conservation, heritage or recreation values, provide innumerable ecosystem services. This paper explores the history of the development of policies for open space systems gazetted by national governments in Ottawa and Canberra, the respective capitals of Canada and Australia. It examines how these cities have approached their metropolitan planning strategies and comments on the way urban landscapes have been accommodated in future growth through strategic plans and policies. In doing so it identifies the challenges faced when urban open spaces, deemed to be of national heritage significance, compete for increasingly scarce government resources and face increasing pressures from urban consolidation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.615

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0210.031
Scholarly communication0.0110.004
Open science0.0010.011
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.362
GPT teacher head0.364
Teacher spread0.002 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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